Hi, my name is Vitor Ferreira.
On this Github I present projects developed from public data, with resolutions of business problems using Data Science concepts and tools.
4+ yrs of experience in the data field: began as a Data Analyst at my own firm in 2019, and currently leading data projects at Dadosfera since 2022. Expertise in data management and problem-solving.
📊 Currently serving in the Professional Services division of a data startup, developing projects related to data analysis, data engineering, and data science.
🚀 Served as a Data Analyst and Commercial Consultant in my own consulting and sales representation company from July 2019 to March 2022. Achieved a 262% growth in sales revenue from 2019 to 2020.
🎯 Extensive experience in people management, communication, and developing solutions for corporate problems.
💻 Data Science & Analytics Skills:
- Programming Languages and Database: Python, SQL, SQLite, Postgres, MySQL.
- Machine Learning: Regression, Classification and Clustering Algorithms.
- Software Engineering: AWS, Git, Github, Virtual Environment.
- Data Viz: Power BI, Tableau, Metabase, Streamlit, Matplotlib, Seaborn
- Soft Skills: Assertiveness, Flexibility, Problem-solving, Teamwork
To deploy a new loyalty program called Insiders, an unsupervised machine learning model of Clustering was developed, grouping the customer base according to their similarities.
To increase the sales team's performance during a Cross Sell campaign, a Classification Machine Learning model was developed to generate a purchase propensity score and classify a base of 127 thousand customers. The trained model generated an extra revenue of $25,000,000.00.
Development of a Machine Learning algorithm to predict sales 6 weeks in advance in a pharmacy chain in Europe. The trained Regression algorithm has 88% MAPE and was made available for queries through a Telegram bot.
A company wants to enter the American men's clothing market and for that, it needs market research of the main competitors in the segment. The project will be developed through web scraping with python.
In this final project of the certification in Data Analytics from Google, the analysis of data from the Cyclistic company was carried out in order to generate insights to increase the conversion rate from casual customers to annual subscribers.
In order to maximize the company's return on investment, this Data Analysis project was developed using Python to identify opportunities for homes below the average market price and define when and at what price to resell these properties.
Development of a Dashboard in Power BI to visualize the evolution of 4 KPI's: Revenue, Sales Quantity, Average Ticket and Positivation. The results are detailed in the project by time period, by product and by collaborator.